Overview

Brought to you by YData

Dataset statistics

Number of variables20
Number of observations45376
Missing cells41134
Missing cells (%)4.5%
Duplicate rows16
Duplicate rows (%)< 0.1%
Total size in memory55.6 MiB
Average record size in memory1.3 KiB

Variable types

Numeric9
Text4
DateTime1
Unsupported5
Categorical1

Alerts

Dataset has 16 (< 0.1%) duplicate rowsDuplicates
budget is highly overall correlated with return and 1 other fieldsHigh correlation
popularity is highly overall correlated with vote_countHigh correlation
return is highly overall correlated with budget and 1 other fieldsHigh correlation
revenue is highly overall correlated with budget and 2 other fieldsHigh correlation
vote_count is highly overall correlated with popularity and 1 other fieldsHigh correlation
status is highly imbalanced (96.6%) Imbalance
belongs_to_collection has 40888 (90.1%) missing values Missing
popularity is highly skewed (γ1 = 29.21506573) Skewed
return is highly skewed (γ1 = 138.3295261) Skewed
genres is an unsupported type, check if it needs cleaning or further analysis Unsupported
production_companies is an unsupported type, check if it needs cleaning or further analysis Unsupported
production_countries is an unsupported type, check if it needs cleaning or further analysis Unsupported
spoken_languages is an unsupported type, check if it needs cleaning or further analysis Unsupported
belongs_to_collection is an unsupported type, check if it needs cleaning or further analysis Unsupported
runtime has 1535 (3.4%) zeros Zeros
budget has 36490 (80.4%) zeros Zeros
revenue has 37969 (83.7%) zeros Zeros
vote_average has 2947 (6.5%) zeros Zeros
vote_count has 2849 (6.3%) zeros Zeros
return has 40057 (88.3%) zeros Zeros

Reproduction

Analysis started2025-02-18 17:13:37.062245
Analysis finished2025-02-18 17:14:24.951472
Duration47.89 seconds
Software versionydata-profiling vv4.12.2
Download configurationconfig.json

Variables

movie_id
Real number (ℝ)

Distinct45346
Distinct (%)99.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean108027.1
Minimum2
Maximum469172
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size354.6 KiB
2025-02-18T12:14:25.066030image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile5348.75
Q126385.75
median59857.5
Q3156533.5
95-th percentile357194.5
Maximum469172
Range469170
Interquartile range (IQR)130147.75

Descriptive statistics

Standard deviation112168.38
Coefficient of variation (CV)1.0383355
Kurtosis0.55951556
Mean108027.1
Median Absolute Deviation (MAD)44418.5
Skewness1.2830689
Sum4.9018378 × 109
Variance1.2581745 × 1010
MonotonicityNot monotonic
2025-02-18T12:14:25.139141image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
141971 3
 
< 0.1%
97995 2
 
< 0.1%
10991 2
 
< 0.1%
109962 2
 
< 0.1%
119916 2
 
< 0.1%
159849 2
 
< 0.1%
84198 2
 
< 0.1%
132641 2
 
< 0.1%
168538 2
 
< 0.1%
99080 2
 
< 0.1%
Other values (45336) 45355
> 99.9%
ValueCountFrequency (%)
2 1
< 0.1%
3 1
< 0.1%
5 1
< 0.1%
6 1
< 0.1%
11 1
< 0.1%
12 1
< 0.1%
13 1
< 0.1%
14 1
< 0.1%
15 1
< 0.1%
16 1
< 0.1%
ValueCountFrequency (%)
469172 1
< 0.1%
468707 1
< 0.1%
468343 1
< 0.1%
467731 1
< 0.1%
465044 1
< 0.1%
464819 1
< 0.1%
464207 1
< 0.1%
464111 1
< 0.1%
463906 1
< 0.1%
463800 1
< 0.1%

title
Text

Distinct42196
Distinct (%)93.0%
Missing0
Missing (%)0.0%
Memory size3.2 MiB
2025-02-18T12:14:25.463982image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/

Length

Max length105
Median length79
Mean length16.701781
Min length1

Characters and Unicode

Total characters757860
Distinct characters287
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique39869 ?
Unique (%)87.9%

Sample

1st rowToy Story
2nd rowJumanji
3rd rowGrumpier Old Men
4th rowWaiting to Exhale
5th rowFather of the Bride Part II
ValueCountFrequency (%)
the 14555
 
10.7%
of 4930
 
3.6%
a 2241
 
1.6%
in 1693
 
1.2%
and 1631
 
1.2%
to 1054
 
0.8%
757
 
0.6%
man 665
 
0.5%
love 664
 
0.5%
for 601
 
0.4%
Other values (24353) 107390
78.9%
2025-02-18T12:14:25.907485image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
90827
 
12.0%
e 76251
 
10.1%
a 48940
 
6.5%
o 45671
 
6.0%
n 40817
 
5.4%
r 40018
 
5.3%
i 39764
 
5.2%
t 36722
 
4.8%
s 29519
 
3.9%
h 28516
 
3.8%
Other values (277) 280815
37.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 757860
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
90827
 
12.0%
e 76251
 
10.1%
a 48940
 
6.5%
o 45671
 
6.0%
n 40817
 
5.4%
r 40018
 
5.3%
i 39764
 
5.2%
t 36722
 
4.8%
s 29519
 
3.9%
h 28516
 
3.8%
Other values (277) 280815
37.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 757860
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
90827
 
12.0%
e 76251
 
10.1%
a 48940
 
6.5%
o 45671
 
6.0%
n 40817
 
5.4%
r 40018
 
5.3%
i 39764
 
5.2%
t 36722
 
4.8%
s 29519
 
3.9%
h 28516
 
3.8%
Other values (277) 280815
37.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 757860
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
90827
 
12.0%
e 76251
 
10.1%
a 48940
 
6.5%
o 45671
 
6.0%
n 40817
 
5.4%
r 40018
 
5.3%
i 39764
 
5.2%
t 36722
 
4.8%
s 29519
 
3.9%
h 28516
 
3.8%
Other values (277) 280815
37.1%
Distinct20270
Distinct (%)44.7%
Missing0
Missing (%)0.0%
Memory size3.5 MiB
2025-02-18T12:14:26.201298image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/

Length

Max length297
Median length3
Mean length22.779134
Min length1

Characters and Unicode

Total characters1033626
Distinct characters170
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique20163 ?
Unique (%)44.4%

Sample

1st rownan
2nd rowRoll the dice and unleash the excitement!
3rd rowStill Yelling. Still Fighting. Still Ready for Love.
4th rowFriends are the people who let you be yourself... and never let you forget it.
5th rowJust When His World Is Back To Normal... He's In For The Surprise Of His Life!
ValueCountFrequency (%)
nan 24978
 
12.6%
the 10998
 
5.5%
a 6815
 
3.4%
of 4404
 
2.2%
to 3584
 
1.8%
is 2796
 
1.4%
in 2693
 
1.4%
and 2682
 
1.3%
you 2389
 
1.2%
1582
 
0.8%
Other values (15101) 135993
68.4%
2025-02-18T12:14:26.577624image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
153686
14.9%
n 97454
 
9.4%
e 94412
 
9.1%
a 76451
 
7.4%
t 57267
 
5.5%
o 56566
 
5.5%
i 46036
 
4.5%
r 44992
 
4.4%
s 42360
 
4.1%
h 37172
 
3.6%
Other values (160) 327230
31.7%

Most occurring categories

ValueCountFrequency (%)
(unknown) 1033626
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
153686
14.9%
n 97454
 
9.4%
e 94412
 
9.1%
a 76451
 
7.4%
t 57267
 
5.5%
o 56566
 
5.5%
i 46036
 
4.5%
r 44992
 
4.4%
s 42360
 
4.1%
h 37172
 
3.6%
Other values (160) 327230
31.7%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 1033626
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
153686
14.9%
n 97454
 
9.4%
e 94412
 
9.1%
a 76451
 
7.4%
t 57267
 
5.5%
o 56566
 
5.5%
i 46036
 
4.5%
r 44992
 
4.4%
s 42360
 
4.1%
h 37172
 
3.6%
Other values (160) 327230
31.7%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 1033626
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
153686
14.9%
n 97454
 
9.4%
e 94412
 
9.1%
a 76451
 
7.4%
t 57267
 
5.5%
o 56566
 
5.5%
i 46036
 
4.5%
r 44992
 
4.4%
s 42360
 
4.1%
h 37172
 
3.6%
Other values (160) 327230
31.7%
Distinct17333
Distinct (%)38.2%
Missing0
Missing (%)0.0%
Memory size354.6 KiB
Minimum1874-12-09 00:00:00
Maximum2020-12-16 00:00:00
Invalid dates0
Invalid dates (%)0.0%
2025-02-18T12:14:26.663874image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2025-02-18T12:14:26.737982image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

release_year
Real number (ℝ)

Distinct135
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1991.8812
Minimum1874
Maximum2020
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size354.6 KiB
2025-02-18T12:14:26.803626image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/

Quantile statistics

Minimum1874
5-th percentile1941
Q11978
median2001
Q32010
95-th percentile2015
Maximum2020
Range146
Interquartile range (IQR)32

Descriptive statistics

Standard deviation24.05536
Coefficient of variation (CV)0.012076704
Kurtosis0.84010576
Mean1991.8812
Median Absolute Deviation (MAD)12
Skewness-1.2248636
Sum90383601
Variance578.66033
MonotonicityNot monotonic
2025-02-18T12:14:26.876562image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2014 1974
 
4.4%
2015 1905
 
4.2%
2013 1889
 
4.2%
2012 1722
 
3.8%
2011 1667
 
3.7%
2016 1604
 
3.5%
2009 1586
 
3.5%
2010 1501
 
3.3%
2008 1473
 
3.2%
2007 1320
 
2.9%
Other values (125) 28735
63.3%
ValueCountFrequency (%)
1874 1
 
< 0.1%
1878 1
 
< 0.1%
1883 1
 
< 0.1%
1887 1
 
< 0.1%
1888 2
 
< 0.1%
1890 5
 
< 0.1%
1891 6
< 0.1%
1892 3
 
< 0.1%
1893 1
 
< 0.1%
1894 13
< 0.1%
ValueCountFrequency (%)
2020 1
 
< 0.1%
2018 5
 
< 0.1%
2017 532
 
1.2%
2016 1604
3.5%
2015 1905
4.2%
2014 1974
4.4%
2013 1889
4.2%
2012 1722
3.8%
2011 1667
3.7%
2010 1501
3.3%

runtime
Real number (ℝ)

Zeros 

Distinct353
Distinct (%)0.8%
Missing246
Missing (%)0.5%
Infinite0
Infinite (%)0.0%
Mean94.181675
Minimum0
Maximum1256
Zeros1535
Zeros (%)3.4%
Negative0
Negative (%)0.0%
Memory size354.6 KiB
2025-02-18T12:14:26.950198image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile12
Q185
median95
Q3107
95-th percentile138
Maximum1256
Range1256
Interquartile range (IQR)22

Descriptive statistics

Standard deviation38.341059
Coefficient of variation (CV)0.4070968
Kurtosis93.925543
Mean94.181675
Median Absolute Deviation (MAD)11
Skewness4.4907363
Sum4250419
Variance1470.0368
MonotonicityNot monotonic
2025-02-18T12:14:27.025644image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
90 2549
 
5.6%
0 1535
 
3.4%
100 1470
 
3.2%
95 1410
 
3.1%
93 1214
 
2.7%
96 1104
 
2.4%
92 1079
 
2.4%
94 1062
 
2.3%
91 1055
 
2.3%
88 1030
 
2.3%
Other values (343) 31622
69.7%
ValueCountFrequency (%)
0 1535
3.4%
1 107
 
0.2%
2 33
 
0.1%
3 48
 
0.1%
4 50
 
0.1%
5 51
 
0.1%
6 72
 
0.2%
7 103
 
0.2%
8 78
 
0.2%
9 63
 
0.1%
ValueCountFrequency (%)
1256 1
< 0.1%
1140 2
< 0.1%
931 1
< 0.1%
925 1
< 0.1%
900 1
< 0.1%
877 1
< 0.1%
874 1
< 0.1%
840 2
< 0.1%
780 1
< 0.1%
720 1
< 0.1%

budget
Real number (ℝ)

High correlation  Zeros 

Distinct1223
Distinct (%)2.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4232604.4
Minimum0
Maximum3.8 × 108
Zeros36490
Zeros (%)80.4%
Negative0
Negative (%)0.0%
Memory size354.6 KiB
2025-02-18T12:14:27.096457image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile25000000
Maximum3.8 × 108
Range3.8 × 108
Interquartile range (IQR)0

Descriptive statistics

Standard deviation17439860
Coefficient of variation (CV)4.1203614
Kurtosis66.634491
Mean4232604.4
Median Absolute Deviation (MAD)0
Skewness7.1183385
Sum1.9205866 × 1011
Variance3.041487 × 1014
MonotonicityNot monotonic
2025-02-18T12:14:27.307270image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 36490
80.4%
5000000 286
 
0.6%
10000000 259
 
0.6%
20000000 243
 
0.5%
2000000 242
 
0.5%
15000000 226
 
0.5%
3000000 223
 
0.5%
25000000 206
 
0.5%
1000000 197
 
0.4%
30000000 190
 
0.4%
Other values (1213) 6814
 
15.0%
ValueCountFrequency (%)
0 36490
80.4%
1 25
 
0.1%
2 14
 
< 0.1%
3 9
 
< 0.1%
4 8
 
< 0.1%
5 8
 
< 0.1%
6 5
 
< 0.1%
7 4
 
< 0.1%
8 5
 
< 0.1%
9 1
 
< 0.1%
ValueCountFrequency (%)
380000000 1
 
< 0.1%
300000000 1
 
< 0.1%
280000000 1
 
< 0.1%
270000000 1
 
< 0.1%
260000000 3
 
< 0.1%
258000000 1
 
< 0.1%
255000000 1
 
< 0.1%
250000000 10
< 0.1%
245000000 2
 
< 0.1%
237000000 1
 
< 0.1%

revenue
Real number (ℝ)

High correlation  Zeros 

Distinct6863
Distinct (%)15.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean11230099
Minimum0
Maximum2.7879651 × 109
Zeros37969
Zeros (%)83.7%
Negative0
Negative (%)0.0%
Memory size354.6 KiB
2025-02-18T12:14:27.379111image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile48020044
Maximum2.7879651 × 109
Range2.7879651 × 109
Interquartile range (IQR)0

Descriptive statistics

Standard deviation64389957
Coefficient of variation (CV)5.7336944
Kurtosis237.07741
Mean11230099
Median Absolute Deviation (MAD)0
Skewness12.254722
Sum5.0957698 × 1011
Variance4.1460665 × 1015
MonotonicityNot monotonic
2025-02-18T12:14:27.447720image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 37969
83.7%
12000000 20
 
< 0.1%
10000000 19
 
< 0.1%
11000000 19
 
< 0.1%
2000000 18
 
< 0.1%
6000000 17
 
< 0.1%
5000000 14
 
< 0.1%
8000000 13
 
< 0.1%
500000 13
 
< 0.1%
1 12
 
< 0.1%
Other values (6853) 7262
 
16.0%
ValueCountFrequency (%)
0 37969
83.7%
1 12
 
< 0.1%
2 3
 
< 0.1%
3 9
 
< 0.1%
4 4
 
< 0.1%
5 5
 
< 0.1%
6 2
 
< 0.1%
7 4
 
< 0.1%
8 5
 
< 0.1%
9 1
 
< 0.1%
ValueCountFrequency (%)
2787965087 1
< 0.1%
2068223624 1
< 0.1%
1845034188 1
< 0.1%
1519557910 1
< 0.1%
1513528810 1
< 0.1%
1506249360 1
< 0.1%
1405403694 1
< 0.1%
1342000000 1
< 0.1%
1274219009 1
< 0.1%
1262886337 1
< 0.1%

genres
Unsupported

Rejected  Unsupported 

Missing0
Missing (%)0.0%
Memory size4.9 MiB

production_companies
Unsupported

Rejected  Unsupported 

Missing0
Missing (%)0.0%
Memory size4.3 MiB

production_countries
Unsupported

Rejected  Unsupported 

Missing0
Missing (%)0.0%
Memory size4.2 MiB

spoken_languages
Unsupported

Rejected  Unsupported 

Missing0
Missing (%)0.0%
Memory size4.3 MiB
Distinct90
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size2.6 MiB
2025-02-18T12:14:27.586758image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/

Length

Max length3
Median length2
Mean length2.0002424
Min length2

Characters and Unicode

Total characters90763
Distinct characters26
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique17 ?
Unique (%)< 0.1%

Sample

1st rowen
2nd rowen
3rd rowen
4th rowen
5th rowen
ValueCountFrequency (%)
en 32202
71.0%
fr 2437
 
5.4%
it 1528
 
3.4%
ja 1349
 
3.0%
de 1078
 
2.4%
es 992
 
2.2%
ru 822
 
1.8%
hi 508
 
1.1%
ko 444
 
1.0%
zh 408
 
0.9%
Other values (80) 3608
 
8.0%
2025-02-18T12:14:27.790328image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 34527
38.0%
n 32932
36.3%
r 3630
 
4.0%
f 2835
 
3.1%
i 2388
 
2.6%
t 2250
 
2.5%
a 1850
 
2.0%
s 1652
 
1.8%
j 1350
 
1.5%
d 1323
 
1.5%
Other values (16) 6026
 
6.6%

Most occurring categories

ValueCountFrequency (%)
(unknown) 90763
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
e 34527
38.0%
n 32932
36.3%
r 3630
 
4.0%
f 2835
 
3.1%
i 2388
 
2.6%
t 2250
 
2.5%
a 1850
 
2.0%
s 1652
 
1.8%
j 1350
 
1.5%
d 1323
 
1.5%
Other values (16) 6026
 
6.6%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 90763
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
e 34527
38.0%
n 32932
36.3%
r 3630
 
4.0%
f 2835
 
3.1%
i 2388
 
2.6%
t 2250
 
2.5%
a 1850
 
2.0%
s 1652
 
1.8%
j 1350
 
1.5%
d 1323
 
1.5%
Other values (16) 6026
 
6.6%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 90763
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
e 34527
38.0%
n 32932
36.3%
r 3630
 
4.0%
f 2835
 
3.1%
i 2388
 
2.6%
t 2250
 
2.5%
a 1850
 
2.0%
s 1652
 
1.8%
j 1350
 
1.5%
d 1323
 
1.5%
Other values (16) 6026
 
6.6%
Distinct44233
Distinct (%)97.5%
Missing0
Missing (%)0.0%
Memory size20.0 MiB
2025-02-18T12:14:28.144810image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/

Length

Max length1000
Median length790
Mean length316.6548
Min length1

Characters and Unicode

Total characters14368528
Distinct characters429
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique44173 ?
Unique (%)97.3%

Sample

1st rowLed by Woody, Andy's toys live happily in his room until Andy's birthday brings Buzz Lightyear onto the scene. Afraid of losing his place in Andy's heart, Woody plots against Buzz. But when circumstances separate Buzz and Woody from their owner, the duo eventually learns to put aside their differences.
2nd rowWhen siblings Judy and Peter discover an enchanted board game that opens the door to a magical world, they unwittingly invite Alan -- an adult who's been trapped inside the game for 26 years -- into their living room. Alan's only hope for freedom is to finish the game, which proves risky as all three find themselves running from giant rhinoceroses, evil monkeys and other terrifying creatures.
3rd rowA family wedding reignites the ancient feud between next-door neighbors and fishing buddies John and Max. Meanwhile, a sultry Italian divorcée opens a restaurant at the local bait shop, alarming the locals who worry she'll scare the fish away. But she's less interested in seafood than she is in cooking up a hot time with Max.
4th rowCheated on, mistreated and stepped on, the women are holding their breath, waiting for the elusive "good man" to break a string of less-than-stellar lovers. Friends and confidants Vannah, Bernie, Glo and Robin talk it all out, determined to find a better way to breathe.
5th rowJust when George Banks has recovered from his daughter's wedding, he receives the news that she's pregnant ... and that George's wife, Nina, is expecting too. He was planning on selling their home, but that's a plan that -- like George -- will have to change with the arrival of both a grandchild and a kid of his own.
ValueCountFrequency (%)
the 138082
 
5.6%
a 98889
 
4.0%
and 75259
 
3.1%
to 73321
 
3.0%
of 69574
 
2.8%
in 48143
 
2.0%
is 36500
 
1.5%
his 36165
 
1.5%
with 23902
 
1.0%
her 21484
 
0.9%
Other values (97091) 1828330
74.6%
2025-02-18T12:14:28.588305image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2406350
16.7%
e 1363787
 
9.5%
a 941443
 
6.6%
t 934766
 
6.5%
i 851514
 
5.9%
o 829873
 
5.8%
n 824483
 
5.7%
s 767851
 
5.3%
r 744274
 
5.2%
h 600810
 
4.2%
Other values (419) 4103377
28.6%

Most occurring categories

ValueCountFrequency (%)
(unknown) 14368528
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
2406350
16.7%
e 1363787
 
9.5%
a 941443
 
6.6%
t 934766
 
6.5%
i 851514
 
5.9%
o 829873
 
5.8%
n 824483
 
5.7%
s 767851
 
5.3%
r 744274
 
5.2%
h 600810
 
4.2%
Other values (419) 4103377
28.6%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 14368528
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
2406350
16.7%
e 1363787
 
9.5%
a 941443
 
6.6%
t 934766
 
6.5%
i 851514
 
5.9%
o 829873
 
5.8%
n 824483
 
5.7%
s 767851
 
5.3%
r 744274
 
5.2%
h 600810
 
4.2%
Other values (419) 4103377
28.6%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 14368528
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
2406350
16.7%
e 1363787
 
9.5%
a 941443
 
6.6%
t 934766
 
6.5%
i 851514
 
5.9%
o 829873
 
5.8%
n 824483
 
5.7%
s 767851
 
5.3%
r 744274
 
5.2%
h 600810
 
4.2%
Other values (419) 4103377
28.6%

popularity
Real number (ℝ)

High correlation  Skewed 

Distinct43731
Distinct (%)96.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.9264576
Minimum0
Maximum547.4883
Zeros40
Zeros (%)0.1%
Negative0
Negative (%)0.0%
Memory size354.6 KiB
2025-02-18T12:14:28.673727image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.02079775
Q10.3888395
median1.1304545
Q33.6916945
95-th percentile11.063627
Maximum547.4883
Range547.4883
Interquartile range (IQR)3.302855

Descriptive statistics

Standard deviation6.0096718
Coefficient of variation (CV)2.0535653
Kurtosis1923.6882
Mean2.9264576
Median Absolute Deviation (MAD)0.9676215
Skewness29.215066
Sum132790.94
Variance36.116156
MonotonicityNot monotonic
2025-02-18T12:14:28.741525image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 × 10-656
 
0.1%
0.000308 42
 
0.1%
0 40
 
0.1%
0.00022 39
 
0.1%
0.000844 38
 
0.1%
0.000578 38
 
0.1%
0.001177 38
 
0.1%
0.002001 27
 
0.1%
0.003013 21
 
< 0.1%
0.00353 19
 
< 0.1%
Other values (43721) 45018
99.2%
ValueCountFrequency (%)
0 40
0.1%
1 × 10-656
0.1%
2 × 10-66
 
< 0.1%
3 × 10-66
 
< 0.1%
4 × 10-65
 
< 0.1%
5 × 10-61
 
< 0.1%
6 × 10-62
 
< 0.1%
7 × 10-61
 
< 0.1%
8 × 10-66
 
< 0.1%
9 × 10-62
 
< 0.1%
ValueCountFrequency (%)
547.488298 1
< 0.1%
294.337037 1
< 0.1%
287.253654 1
< 0.1%
228.032744 1
< 0.1%
213.849907 1
< 0.1%
187.860492 1
< 0.1%
185.330992 1
< 0.1%
185.070892 1
< 0.1%
183.870374 1
< 0.1%
154.801009 1
< 0.1%

vote_average
Real number (ℝ)

Zeros 

Distinct92
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5.62407
Minimum0
Maximum10
Zeros2947
Zeros (%)6.5%
Negative0
Negative (%)0.0%
Memory size354.6 KiB
2025-02-18T12:14:28.813428image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q15
median6
Q36.8
95-th percentile7.8
Maximum10
Range10
Interquartile range (IQR)1.8

Descriptive statistics

Standard deviation1.9154225
Coefficient of variation (CV)0.34057587
Kurtosis2.5420547
Mean5.62407
Median Absolute Deviation (MAD)0.9
Skewness-1.524472
Sum255197.8
Variance3.6688434
MonotonicityNot monotonic
2025-02-18T12:14:28.886408image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 2947
 
6.5%
6 2462
 
5.4%
5 1998
 
4.4%
7 1883
 
4.1%
6.5 1722
 
3.8%
6.3 1603
 
3.5%
5.5 1381
 
3.0%
5.8 1369
 
3.0%
6.4 1350
 
3.0%
6.7 1342
 
3.0%
Other values (82) 27319
60.2%
ValueCountFrequency (%)
0 2947
6.5%
0.5 13
 
< 0.1%
0.7 1
 
< 0.1%
1 103
 
0.2%
1.1 1
 
< 0.1%
1.2 4
 
< 0.1%
1.3 13
 
< 0.1%
1.4 5
 
< 0.1%
1.5 30
 
0.1%
1.6 6
 
< 0.1%
ValueCountFrequency (%)
10 185
0.4%
9.8 1
 
< 0.1%
9.6 1
 
< 0.1%
9.5 18
 
< 0.1%
9.4 3
 
< 0.1%
9.3 18
 
< 0.1%
9.2 4
 
< 0.1%
9.1 2
 
< 0.1%
9 158
0.3%
8.9 7
 
< 0.1%

vote_count
Real number (ℝ)

High correlation  Zeros 

Distinct1820
Distinct (%)4.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean110.09644
Minimum0
Maximum14075
Zeros2849
Zeros (%)6.3%
Negative0
Negative (%)0.0%
Memory size354.6 KiB
2025-02-18T12:14:28.953718image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q13
median10
Q334
95-th percentile434
Maximum14075
Range14075
Interquartile range (IQR)31

Descriptive statistics

Standard deviation491.74289
Coefficient of variation (CV)4.4664741
Kurtosis150.92858
Mean110.09644
Median Absolute Deviation (MAD)8
Skewness10.440782
Sum4995736
Variance241811.07
MonotonicityNot monotonic
2025-02-18T12:14:29.024623image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 3242
 
7.1%
2 3127
 
6.9%
0 2849
 
6.3%
3 2785
 
6.1%
4 2478
 
5.5%
5 2097
 
4.6%
6 1747
 
3.9%
7 1570
 
3.5%
8 1359
 
3.0%
9 1194
 
2.6%
Other values (1810) 22928
50.5%
ValueCountFrequency (%)
0 2849
6.3%
1 3242
7.1%
2 3127
6.9%
3 2785
6.1%
4 2478
5.5%
5 2097
4.6%
6 1747
3.9%
7 1570
3.5%
8 1359
3.0%
9 1194
 
2.6%
ValueCountFrequency (%)
14075 1
< 0.1%
12269 1
< 0.1%
12114 1
< 0.1%
12000 1
< 0.1%
11444 1
< 0.1%
11187 1
< 0.1%
10297 1
< 0.1%
10014 1
< 0.1%
9678 1
< 0.1%
9634 1
< 0.1%

belongs_to_collection
Unsupported

Missing  Rejected  Unsupported 

Missing40888
Missing (%)90.1%
Memory size2.3 MiB

status
Categorical

Imbalance 

Distinct7
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.8 MiB
Released
44936 
Rumored
 
230
Post Production
 
97
nan
 
80
In Production
 
19
Other values (2)
 
14

Length

Max length15
Median length8
Mean length8.002887
Min length3

Characters and Unicode

Total characters363139
Distinct characters18
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st rowReleased
2nd rowReleased
3rd rowReleased
4th rowReleased
5th rowReleased

Common Values

ValueCountFrequency (%)
Released 44936
99.0%
Rumored 230
 
0.5%
Post Production 97
 
0.2%
nan 80
 
0.2%
In Production 19
 
< 0.1%
Planned 13
 
< 0.1%
Canceled 1
 
< 0.1%

Length

2025-02-18T12:14:29.093402image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-02-18T12:14:29.155583image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
ValueCountFrequency (%)
released 44936
98.8%
rumored 230
 
0.5%
production 116
 
0.3%
post 97
 
0.2%
nan 80
 
0.2%
in 19
 
< 0.1%
planned 13
 
< 0.1%
canceled 1
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
e 135053
37.2%
d 45296
 
12.5%
R 45166
 
12.4%
s 45033
 
12.4%
a 45030
 
12.4%
l 44950
 
12.4%
o 559
 
0.2%
r 346
 
0.1%
u 346
 
0.1%
n 322
 
0.1%
Other values (8) 1038
 
0.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 363139
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
e 135053
37.2%
d 45296
 
12.5%
R 45166
 
12.4%
s 45033
 
12.4%
a 45030
 
12.4%
l 44950
 
12.4%
o 559
 
0.2%
r 346
 
0.1%
u 346
 
0.1%
n 322
 
0.1%
Other values (8) 1038
 
0.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 363139
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
e 135053
37.2%
d 45296
 
12.5%
R 45166
 
12.4%
s 45033
 
12.4%
a 45030
 
12.4%
l 44950
 
12.4%
o 559
 
0.2%
r 346
 
0.1%
u 346
 
0.1%
n 322
 
0.1%
Other values (8) 1038
 
0.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 363139
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
e 135053
37.2%
d 45296
 
12.5%
R 45166
 
12.4%
s 45033
 
12.4%
a 45030
 
12.4%
l 44950
 
12.4%
o 559
 
0.2%
r 346
 
0.1%
u 346
 
0.1%
n 322
 
0.1%
Other values (8) 1038
 
0.3%

return
Real number (ℝ)

High correlation  Skewed  Zeros 

Distinct1256
Distinct (%)2.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean660.04279
Minimum0
Maximum12396383
Zeros40057
Zeros (%)88.3%
Negative0
Negative (%)0.0%
Memory size354.6 KiB
2025-02-18T12:14:29.223614image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile2.54
Maximum12396383
Range12396383
Interquartile range (IQR)0

Descriptive statistics

Standard deviation74693.294
Coefficient of variation (CV)113.16432
Kurtosis20672.957
Mean660.04279
Median Absolute Deviation (MAD)0
Skewness138.32953
Sum29950102
Variance5.5790882 × 109
MonotonicityNot monotonic
2025-02-18T12:14:29.299893image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 40057
88.3%
0.01 64
 
0.1%
0.02 38
 
0.1%
1 34
 
0.1%
0.08 29
 
0.1%
0.06 27
 
0.1%
0.03 25
 
0.1%
0.62 25
 
0.1%
1.1 24
 
0.1%
1.2 23
 
0.1%
Other values (1246) 5030
 
11.1%
ValueCountFrequency (%)
0 40057
88.3%
0.01 64
 
0.1%
0.02 38
 
0.1%
0.03 25
 
0.1%
0.04 19
 
< 0.1%
0.05 22
 
< 0.1%
0.06 27
 
0.1%
0.07 18
 
< 0.1%
0.08 29
 
0.1%
0.09 16
 
< 0.1%
ValueCountFrequency (%)
12396383 1
< 0.1%
8500000 1
< 0.1%
4197476.62 1
< 0.1%
2755584 1
< 0.1%
1018619.28 1
< 0.1%
1000000 1
< 0.1%
26881.72 1
< 0.1%
12890.39 1
< 0.1%
5330.34 1
< 0.1%
4133.33 1
< 0.1%

Interactions

2025-02-18T12:14:23.904771image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2025-02-18T12:14:19.369829image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2025-02-18T12:14:20.090107image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2025-02-18T12:14:20.611845image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2025-02-18T12:14:21.116132image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2025-02-18T12:14:21.642577image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2025-02-18T12:14:22.143221image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2025-02-18T12:14:22.690101image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2025-02-18T12:14:23.253866image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2025-02-18T12:14:23.960791image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2025-02-18T12:14:19.648193image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2025-02-18T12:14:20.143997image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2025-02-18T12:14:20.664828image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2025-02-18T12:14:21.168949image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2025-02-18T12:14:21.703374image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2025-02-18T12:14:22.199401image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2025-02-18T12:14:22.761310image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2025-02-18T12:14:23.443026image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2025-02-18T12:14:24.018275image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2025-02-18T12:14:19.707408image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2025-02-18T12:14:20.203843image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2025-02-18T12:14:20.723258image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2025-02-18T12:14:21.230862image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2025-02-18T12:14:21.760940image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2025-02-18T12:14:22.256298image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2025-02-18T12:14:22.848893image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2025-02-18T12:14:23.501558image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2025-02-18T12:14:24.075746image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2025-02-18T12:14:19.761084image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2025-02-18T12:14:20.261679image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2025-02-18T12:14:20.778983image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2025-02-18T12:14:21.286857image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2025-02-18T12:14:21.814454image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2025-02-18T12:14:22.348813image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2025-02-18T12:14:22.917889image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2025-02-18T12:14:23.559651image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2025-02-18T12:14:24.134903image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2025-02-18T12:14:19.817898image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2025-02-18T12:14:20.323730image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2025-02-18T12:14:20.836631image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2025-02-18T12:14:21.348100image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2025-02-18T12:14:21.872387image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2025-02-18T12:14:22.406403image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2025-02-18T12:14:22.981224image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2025-02-18T12:14:23.619020image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2025-02-18T12:14:24.189895image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2025-02-18T12:14:19.872365image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2025-02-18T12:14:20.382074image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2025-02-18T12:14:20.894913image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2025-02-18T12:14:21.403747image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2025-02-18T12:14:21.925432image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2025-02-18T12:14:22.458959image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2025-02-18T12:14:23.035978image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2025-02-18T12:14:23.675750image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2025-02-18T12:14:24.244507image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2025-02-18T12:14:19.924725image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2025-02-18T12:14:20.438135image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2025-02-18T12:14:20.947736image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2025-02-18T12:14:21.459276image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2025-02-18T12:14:21.978181image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2025-02-18T12:14:22.510800image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2025-02-18T12:14:23.089272image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2025-02-18T12:14:23.731869image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2025-02-18T12:14:24.296418image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2025-02-18T12:14:19.977205image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2025-02-18T12:14:20.493381image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2025-02-18T12:14:21.001837image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2025-02-18T12:14:21.517712image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2025-02-18T12:14:22.030897image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2025-02-18T12:14:22.562678image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2025-02-18T12:14:23.141923image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2025-02-18T12:14:23.788889image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2025-02-18T12:14:24.355088image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2025-02-18T12:14:20.034251image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2025-02-18T12:14:20.553875image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2025-02-18T12:14:21.059914image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2025-02-18T12:14:21.577084image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2025-02-18T12:14:22.087709image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2025-02-18T12:14:22.624459image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2025-02-18T12:14:23.199107image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2025-02-18T12:14:23.848546image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/

Correlations

2025-02-18T12:14:29.353120image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
budgetmovie_idpopularityrelease_yearreturnrevenueruntimestatusvote_averagevote_count
budget1.000-0.2550.4630.1410.7710.6440.2270.0000.0720.484
movie_id-0.2551.000-0.4100.392-0.263-0.278-0.2050.053-0.149-0.433
popularity0.463-0.4101.0000.1860.4460.4910.3070.0000.2410.893
release_year0.1410.3920.1861.0000.0850.1040.0340.027-0.0090.197
return0.771-0.2630.4460.0851.0000.8490.2340.0000.1210.473
revenue0.644-0.2780.4910.1040.8491.0000.2540.0000.1270.513
runtime0.227-0.2050.3070.0340.2340.2541.0000.0000.1930.290
status0.0000.0530.0000.0270.0000.0000.0001.0000.0250.000
vote_average0.072-0.1490.241-0.0090.1210.1270.1930.0251.0000.318
vote_count0.484-0.4330.8930.1970.4730.5130.2900.0000.3181.000

Missing values

2025-02-18T12:14:24.461868image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
A simple visualization of nullity by column.
2025-02-18T12:14:24.645703image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.
2025-02-18T12:14:24.856723image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

movie_idtitletaglinerelease_daterelease_yearruntimebudgetrevenuegenresproduction_companiesproduction_countriesspoken_languagesoriginal_languageoverviewpopularityvote_averagevote_countbelongs_to_collectionstatusreturn
0862Toy Storynan1995-10-30199581.030000000373554033[{'id': 16, 'name': 'Animation'}, {'id': 35, 'name': 'Comedy'}, {'id': 10751, 'name': 'Family'}][{'name': 'Pixar Animation Studios', 'id': 3}][{'iso_3166_1': 'US', 'name': 'United States of America'}][{'iso_639_1': 'en', 'name': 'English'}]enLed by Woody, Andy's toys live happily in his room until Andy's birthday brings Buzz Lightyear onto the scene. Afraid of losing his place in Andy's heart, Woody plots against Buzz. But when circumstances separate Buzz and Woody from their owner, the duo eventually learns to put aside their differences.21.9469437.75415.0{'id': 10194, 'name': 'Toy Story Collection', 'poster_path': '/7G9915LfUQ2lVfwMEEhDsn3kT4B.jpg', 'backdrop_path': '/9FBwqcd9IRruEDUrTdcaafOMKUq.jpg'}Released12.45
18844JumanjiRoll the dice and unleash the excitement!1995-12-151995104.065000000262797249[{'id': 12, 'name': 'Adventure'}, {'id': 14, 'name': 'Fantasy'}, {'id': 10751, 'name': 'Family'}][{'name': 'TriStar Pictures', 'id': 559}, {'name': 'Teitler Film', 'id': 2550}, {'name': 'Interscope Communications', 'id': 10201}][{'iso_3166_1': 'US', 'name': 'United States of America'}][{'iso_639_1': 'en', 'name': 'English'}, {'iso_639_1': 'fr', 'name': 'Français'}]enWhen siblings Judy and Peter discover an enchanted board game that opens the door to a magical world, they unwittingly invite Alan -- an adult who's been trapped inside the game for 26 years -- into their living room. Alan's only hope for freedom is to finish the game, which proves risky as all three find themselves running from giant rhinoceroses, evil monkeys and other terrifying creatures.17.0155396.92413.0NaNReleased4.04
215602Grumpier Old MenStill Yelling. Still Fighting. Still Ready for Love.1995-12-221995101.000[{'id': 10749, 'name': 'Romance'}, {'id': 35, 'name': 'Comedy'}][{'name': 'Warner Bros.', 'id': 6194}, {'name': 'Lancaster Gate', 'id': 19464}][{'iso_3166_1': 'US', 'name': 'United States of America'}][{'iso_639_1': 'en', 'name': 'English'}]enA family wedding reignites the ancient feud between next-door neighbors and fishing buddies John and Max. Meanwhile, a sultry Italian divorcée opens a restaurant at the local bait shop, alarming the locals who worry she'll scare the fish away. But she's less interested in seafood than she is in cooking up a hot time with Max.11.7129006.592.0{'id': 119050, 'name': 'Grumpy Old Men Collection', 'poster_path': '/nLvUdqgPgm3F85NMCii9gVFUcet.jpg', 'backdrop_path': '/hypTnLot2z8wpFS7qwsQHW1uV8u.jpg'}Released0.00
331357Waiting to ExhaleFriends are the people who let you be yourself... and never let you forget it.1995-12-221995127.01600000081452156[{'id': 35, 'name': 'Comedy'}, {'id': 18, 'name': 'Drama'}, {'id': 10749, 'name': 'Romance'}][{'name': 'Twentieth Century Fox Film Corporation', 'id': 306}][{'iso_3166_1': 'US', 'name': 'United States of America'}][{'iso_639_1': 'en', 'name': 'English'}]enCheated on, mistreated and stepped on, the women are holding their breath, waiting for the elusive "good man" to break a string of less-than-stellar lovers. Friends and confidants Vannah, Bernie, Glo and Robin talk it all out, determined to find a better way to breathe.3.8594956.134.0NaNReleased5.09
411862Father of the Bride Part IIJust When His World Is Back To Normal... He's In For The Surprise Of His Life!1995-02-101995106.0076578911[{'id': 35, 'name': 'Comedy'}][{'name': 'Sandollar Productions', 'id': 5842}, {'name': 'Touchstone Pictures', 'id': 9195}][{'iso_3166_1': 'US', 'name': 'United States of America'}][{'iso_639_1': 'en', 'name': 'English'}]enJust when George Banks has recovered from his daughter's wedding, he receives the news that she's pregnant ... and that George's wife, Nina, is expecting too. He was planning on selling their home, but that's a plan that -- like George -- will have to change with the arrival of both a grandchild and a kid of his own.8.3875195.7173.0{'id': 96871, 'name': 'Father of the Bride Collection', 'poster_path': '/nts4iOmNnq7GNicycMJ9pSAn204.jpg', 'backdrop_path': '/7qwE57OVZmMJChBpLEbJEmzUydk.jpg'}Released0.00
5949HeatA Los Angeles Crime Saga1995-12-151995170.060000000187436818[{'id': 28, 'name': 'Action'}, {'id': 80, 'name': 'Crime'}, {'id': 18, 'name': 'Drama'}, {'id': 53, 'name': 'Thriller'}][{'name': 'Regency Enterprises', 'id': 508}, {'name': 'Forward Pass', 'id': 675}, {'name': 'Warner Bros.', 'id': 6194}][{'iso_3166_1': 'US', 'name': 'United States of America'}][{'iso_639_1': 'en', 'name': 'English'}, {'iso_639_1': 'es', 'name': 'Español'}]enObsessive master thief, Neil McCauley leads a top-notch crew on various insane heists throughout Los Angeles while a mentally unstable detective, Vincent Hanna pursues him without rest. Each man recognizes and respects the ability and the dedication of the other even though they are aware their cat-and-mouse game may end in violence.17.9249277.71886.0NaNReleased3.12
611860SabrinaYou are cordially invited to the most surprising merger of the year.1995-12-151995127.0580000000[{'id': 35, 'name': 'Comedy'}, {'id': 10749, 'name': 'Romance'}][{'name': 'Paramount Pictures', 'id': 4}, {'name': 'Scott Rudin Productions', 'id': 258}, {'name': 'Mirage Enterprises', 'id': 932}, {'name': 'Sandollar Productions', 'id': 5842}, {'name': 'Constellation Entertainment', 'id': 14941}, {'name': 'Worldwide', 'id': 55873}, {'name': 'Mont Blanc Entertainment GmbH', 'id': 58079}][{'iso_3166_1': 'DE', 'name': 'Germany'}, {'iso_3166_1': 'US', 'name': 'United States of America'}][{'iso_639_1': 'fr', 'name': 'Français'}, {'iso_639_1': 'en', 'name': 'English'}]enAn ugly duckling having undergone a remarkable change, still harbors feelings for her crush: a carefree playboy, but not before his business-focused brother has something to say about it.6.6772776.2141.0NaNReleased0.00
745325Tom and HuckThe Original Bad Boys.1995-12-22199597.000[{'id': 28, 'name': 'Action'}, {'id': 12, 'name': 'Adventure'}, {'id': 18, 'name': 'Drama'}, {'id': 10751, 'name': 'Family'}][{'name': 'Walt Disney Pictures', 'id': 2}][{'iso_3166_1': 'US', 'name': 'United States of America'}][{'iso_639_1': 'en', 'name': 'English'}, {'iso_639_1': 'de', 'name': 'Deutsch'}]enA mischievous young boy, Tom Sawyer, witnesses a murder by the deadly Injun Joe. Tom becomes friends with Huckleberry Finn, a boy with no future and no family. Tom has to choose between honoring a friendship or honoring an oath because the town alcoholic is accused of the murder. Tom and Huck go through several adventures trying to retrieve evidence.2.5611615.445.0NaNReleased0.00
89091Sudden DeathTerror goes into overtime.1995-12-221995106.03500000064350171[{'id': 28, 'name': 'Action'}, {'id': 12, 'name': 'Adventure'}, {'id': 53, 'name': 'Thriller'}][{'name': 'Universal Pictures', 'id': 33}, {'name': 'Imperial Entertainment', 'id': 21437}, {'name': 'Signature Entertainment', 'id': 23770}][{'iso_3166_1': 'US', 'name': 'United States of America'}][{'iso_639_1': 'en', 'name': 'English'}]enInternational action superstar Jean Claude Van Damme teams with Powers Boothe in a Tension-packed, suspense thriller, set against the back-drop of a Stanley Cup game.Van Damme portrays a father whose daughter is suddenly taken during a championship hockey game. With the captors demanding a billion dollars by game's end, Van Damme frantically sets a plan in motion to rescue his daughter and abort an impending explosion before the final buzzer...5.2315805.5174.0NaNReleased1.84
9710GoldenEyeNo limits. No fears. No substitutes.1995-11-161995130.058000000352194034[{'id': 12, 'name': 'Adventure'}, {'id': 28, 'name': 'Action'}, {'id': 53, 'name': 'Thriller'}][{'name': 'United Artists', 'id': 60}, {'name': 'Eon Productions', 'id': 7576}][{'iso_3166_1': 'GB', 'name': 'United Kingdom'}, {'iso_3166_1': 'US', 'name': 'United States of America'}][{'iso_639_1': 'en', 'name': 'English'}, {'iso_639_1': 'ru', 'name': 'Pусский'}, {'iso_639_1': 'es', 'name': 'Español'}]enJames Bond must unmask the mysterious head of the Janus Syndicate and prevent the leader from utilizing the GoldenEye weapons system to inflict devastating revenge on Britain.14.6860366.61194.0{'id': 645, 'name': 'James Bond Collection', 'poster_path': '/HORpg5CSkmeQlAolx3bKMrKgfi.jpg', 'backdrop_path': '/6VcVl48kNKvdXOZfJPdarlUGOsk.jpg'}Released6.07
movie_idtitletaglinerelease_daterelease_yearruntimebudgetrevenuegenresproduction_companiesproduction_countriesspoken_languagesoriginal_languageoverviewpopularityvote_averagevote_countbelongs_to_collectionstatusreturn
4536667179St. Michael Had a Roosternan1972-01-01197290.000[][][][{'iso_639_1': 'it', 'name': 'Italiano'}]itSentenced to life imprisonment for illegal activities, Italian International member Giulio Manieri holds on to his political ideals while struggling against madness in the loneliness of his prison cell.0.2250516.03.0NaNReleased0.0
4536784419House of HorrorsMeet...The CREEPER!1946-03-29194665.000[{'id': 27, 'name': 'Horror'}, {'id': 9648, 'name': 'Mystery'}, {'id': 53, 'name': 'Thriller'}][{'name': 'Universal Pictures', 'id': 33}][{'iso_3166_1': 'US', 'name': 'United States of America'}][{'iso_639_1': 'en', 'name': 'English'}]enAn unsuccessful sculptor saves a madman named "The Creeper" from drowning. Seeing an opportunity for revenge, he tricks the psycho into murdering his critics.0.2228146.38.0NaNReleased0.0
45368390959Shadow of the Blair Witchnan2000-10-22200045.000[{'id': 9648, 'name': 'Mystery'}, {'id': 27, 'name': 'Horror'}][][][{'iso_639_1': 'en', 'name': 'English'}]enIn this true-crime documentary, we delve into the murder spree that was the inspiration for Joe Berlinger's "Book of Shadows: Blair Witch 2".0.0760617.02.0NaNReleased0.0
45369289923The Burkittsville 7Do you know what happened 50 years before "The Blair Witch Project"?2000-10-03200030.000[{'id': 27, 'name': 'Horror'}][{'name': 'Neptune Salad Entertainment', 'id': 27570}, {'name': 'Pirie Productions', 'id': 27571}][{'iso_3166_1': 'US', 'name': 'United States of America'}][{'iso_639_1': 'en', 'name': 'English'}]enA film archivist revisits the story of Rustin Parr, a hermit thought to have murdered seven children while under the possession of the Blair Witch.0.3864507.01.0NaNReleased0.0
45370222848Caged Heat 3000nan1995-01-01199585.000[{'id': 878, 'name': 'Science Fiction'}][{'name': 'Concorde-New Horizons', 'id': 4688}][{'iso_3166_1': 'US', 'name': 'United States of America'}][{'iso_639_1': 'en', 'name': 'English'}]enIt's the year 3000 AD. The world's most dangerous women are banished to a remote asteroid 45 million light years from earth. Kira Murphy doesn't belong; wrongfully accused of a crime she did not commit, she's thrown in this interplanetary prison and left to her own defenses. But Kira's a fighter, and soon she finds herself in the middle of a female gang war; where everyone wants a piece of the action... and a piece of her! "Caged Heat 3000" takes the Women-in-Prison genre to a whole new level... and a whole new galaxy!0.6615583.51.0NaNReleased0.0
4537130840Robin Hoodnan1991-05-131991104.000[{'id': 18, 'name': 'Drama'}, {'id': 28, 'name': 'Action'}, {'id': 10749, 'name': 'Romance'}][{'name': 'Westdeutscher Rundfunk (WDR)', 'id': 7025}, {'name': 'Working Title Films', 'id': 10163}, {'name': '20th Century Fox Television', 'id': 16323}, {'name': 'CanWest Global Communications', 'id': 38978}][{'iso_3166_1': 'CA', 'name': 'Canada'}, {'iso_3166_1': 'DE', 'name': 'Germany'}, {'iso_3166_1': 'GB', 'name': 'United Kingdom'}, {'iso_3166_1': 'US', 'name': 'United States of America'}][{'iso_639_1': 'en', 'name': 'English'}]enYet another version of the classic epic, with enough variation to make it interesting. The story is the same, but some of the characters are quite different from the usual, in particular Uma Thurman's very special maid Marian. The photography is also great, giving the story a somewhat darker tone.5.6837535.726.0NaNReleased0.0
45372111109Century of Birthingnan2011-11-172011360.000[{'id': 18, 'name': 'Drama'}][{'name': 'Sine Olivia', 'id': 19653}][{'iso_3166_1': 'PH', 'name': 'Philippines'}][{'iso_639_1': 'tl', 'name': ''}]tlAn artist struggles to finish his work while a storyline about a cult plays in his head.0.1782419.03.0NaNReleased0.0
4537367758BetrayalA deadly game of wits.2003-08-01200390.000[{'id': 28, 'name': 'Action'}, {'id': 18, 'name': 'Drama'}, {'id': 53, 'name': 'Thriller'}][{'name': 'American World Pictures', 'id': 6165}][{'iso_3166_1': 'US', 'name': 'United States of America'}][{'iso_639_1': 'en', 'name': 'English'}]enWhen one of her hits goes wrong, a professional assassin ends up with a suitcase full of a million dollars belonging to a mob boss ...0.9030073.86.0NaNReleased0.0
45374227506Satan Triumphantnan1917-10-21191787.000[][{'name': 'Yermoliev', 'id': 88753}][{'iso_3166_1': 'RU', 'name': 'Russia'}][]enIn a small town live two brothers, one a minister and the other one a hunchback painter of the chapel who lives with his wife. One dreadful and stormy night, a stranger knocks at the door asking for shelter. The stranger talks about all the good things of the earthly life the minister is missing because of his puritanical faith. The minister comes to accept the stranger's viewpoint but it is others who will pay the consequences because the minister will discover the human pleasures thanks to, ehem, his sister- in -law… The tormented minister and his cuckolded brother will die in a strange accident in the chapel and later an infant will be born from the minister's adulterous relationship.0.0035030.00.0NaNReleased0.0
45375461257Queeramanan2017-06-09201775.000[][][{'iso_3166_1': 'GB', 'name': 'United Kingdom'}][{'iso_639_1': 'en', 'name': 'English'}]en50 years after decriminalisation of homosexuality in the UK, director Daisy Asquith mines the jewels of the BFI archive to take us into the relationships, desires, fears and expressions of gay men and women in the 20th century.0.1630150.00.0NaNReleased0.0

Duplicate rows

Most frequently occurring

movie_idtitletaglinerelease_daterelease_yearruntimebudgetrevenueoriginal_languageoverviewpopularityvote_averagevote_countstatusreturn# duplicates
10141971BlackoutWhich one is the first to return - memory or the murderer?2008-12-262008108.000fiRecovering from a nail gun shot to the head and 13 months of coma, doctor Pekka Valinta starts to unravel the mystery of his past, still suffering from total amnesia.0.4119496.73.0Released0.03
05511Le SamouraïThere is no solitude greater than that of the Samurai1967-10-251967105.0039481frHitman Jef Costello is a perfectionist who always carefully plans his murders and who never gets caught.9.0912887.9187.0Released0.02
111115Dealnan2008-01-29200885.000enAs an ex-gambler teaches a hot-shot college kid some things about playing cards, he finds himself pulled into the world series of poker, where his protégé is his toughest competition.6.8803655.222.0Released0.02
218440Days of Darknessnan2007-01-01200789.000enWhen a comet strikes Earth and kicks up a cloud of toxic dust, hundreds of humans join the ranks of the living dead. But there's bad news for the survivors: The newly minted zombies are hell-bent on eradicating every last person from the planet. For the few human beings who remain, going head to head with the flesh-eating fiends is their only chance for long-term survival. Yet their battle will be dark and cold, with overwhelming odds.1.4360855.05.0Released0.02
323305The Warriornan2001-09-23200186.000enIn feudal India, a warrior (Khan) who renounces his role as the longtime enforcer to a local lord becomes the prey in a murderous hunt through the Himalayan mountains.1.9679926.315.0Released0.02
425541Brotherhoodnan2009-10-21200990.000daFormer Danish servicemen Lars and Jimmy are thrown together while training in a neo-Nazi group. Moving from hostility through grudging admiration to friendship and finally passion, events take a darker turn when their illicit relationship is uncovered.2.5879117.121.0Released0.02
542495King Learnan1971-02-041971137.000enKing Lear, old and tired, divides his kingdom among his daughters, giving great importance to their protestations of love for him. When Cordelia, youngest and most honest, refuses to idly flatter the old man in return for favor, he banishes her and turns for support to his remaining daughters. But Goneril and Regan have no love for him and instead plot to take all his power from him. In a parallel, Lear's loyal courtier Gloucester favors his illegitimate son Edmund after being told lies about his faithful son Edgar. Madness and tragedy befall both ill-starred fathers.0.1879018.03.0Rumored0.02
697995Seven Years Bad Lucknan1921-02-06192162.000enAfter breaking a mirror in his home, superstitious Max tries to avoid situations which could bring bad luck but in doing so, causes himself the worst luck imaginable.0.1415585.64.0Released0.02
799080The VikingActually produced during the Great Newfoundland Seal Hunt and You see the REAL thing1931-06-21193170.000enOriginally called White Thunder, American producer Varick Frissell's 1931 film was inspired by his love for the Canadian Arctic Circle. Set in a beautifully black-and-white filmed Newfoundland, it is the story of a rivalry between two seal hunters that plays out on the ice floes during a hunt. Unsatisfied with the first cut, Frissell arranged for the crew to accompany an actual Newfoundland seal hunt on The SS Viking, on which an explosion of dynamite (carried regularly at the time on Arctic ships to combat ice jams) killed many members of the crew, including Frissell. The film was renamed in honor of the dead.0.0023620.00.0Released0.02
8105045The PromiseA love, a hope, a wall.1995-02-161995115.000deEast-Berlin, 1961, shortly after the erection of the Wall. Konrad, Sophie and three of their friends plan a daring escape to Western Germany. The attempt is successful, except for Konrad, who remains behind. From then on, and for the next 28 years, Konrad and Sophie will attempt to meet again, in spite of the Iron Curtain. Konrad, who has become a reputed Astrophysicist, tries to take advantage of scientific congresses outside Eastern Germany to arrange encounters with Sophie. But in a country where the political police, the Stasi, monitors the moves of all suspicious people (such as Konrad's sister Barbara and her husband Harald), preserving one's privacy, ideals and self-respect becomes an exhausting fight, even as the Eastern block begins its long process of disintegration.0.1221785.01.0Released0.02